Global robust stability for delayed neural networks with polytopic type uncertainties

Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.chaos.2005.04.005

Title:	Global robust stability for delayed neural networks with polytopic type uncertainties
Authors:	He, Y. Wang, Q.-G. Zheng, W.-X.
Issue Date:	Dec-2005
Citation:	He, Y., Wang, Q.-G., Zheng, W.-X. (2005-12). Global robust stability for delayed neural networks with polytopic type uncertainties. Chaos, Solitons and Fractals 26 (5) : 1349-1354. ScholarBank@NUS Repository. https://doi.org/10.1016/j.chaos.2005.04.005
Abstract:	In this paper, global robust stability for delayed neural networks is studied. First the free-weighting matrices are employed to express the relationship between the terms in the system equation, and a stability condition for delayed neural networks is derived by using the S-procedure. Then this result is extended to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. A numerical example given in [IEEE Trans Circuits Syst II 52 (2005) 33-36] for interval delayed neural networks is investigated. The effectiveness of the presented global robust stability criterion and its improvement over the existing results are demonstrated. © 2005 Elsevier Ltd. All rights reserved.
Source Title:	Chaos, Solitons and Fractals
URI:	http://scholarbank.nus.edu.sg/handle/10635/56151
ISSN:	09600779
DOI:	10.1016/j.chaos.2005.04.005
Appears in Collections:	Staff Publications

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